Predictive Analytics & Business Insights: 
Practical Uses in eCommerce & Marketing

A/B testing is the best way to optimize the customer experience, select acquisition channels and allocate investments; however, customer segmentation, identification of risk and potential and close monitoring of testing performance are essential components of the strategy. Predictive models can be of great help, as these can identify likely customer shopping behaviors, or they can rank channels based on several factors. These can then be run through tests to determine winning customer experiences. Predictive models can be simple and easy to implement, as in macro investment allocation; they can also be elaborated as in deeper customer segmentation. 

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Mario Vinasco
Data Scientist, Marketing Analytics
Mario Vinasco has over 18 years of progressive experience in data driven analytics with emphasis in database programming and predictive models creatively applied to eCommerce, advertising, customer acquisition/retention and marketing investment.  Mario specializes in developing and applying leading edge business analytics to complex business problems Mario holds a Masters in Engineering economics from Stanford University and currently works for facebook as data scientist; In this role he has been providing optimization recommendations to internal search and other critical IT operations. Prior roles included VP of business intelligence in digital textbook startup, people analytics manager at Google and eCommerce Sr manager at Symantec.

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